Mitigating Adversarial Perturbations for Deep Reinforcement Learning via Vector Quantization

4 October 2024

Thanh Nguyen

Chang D. Yoo

Papers citing "Mitigating Adversarial Perturbations for Deep Reinforcement Learning via Vector Quantization"

21 / 21 papers shown

Title
Diffusion Models for Adversarial Purification Weili Nie Brandon Guo Yujia Huang Chaowei Xiao Arash Vahdat Anima Anandkumar WIGM 250 439 0 16 May 2022
A Minimalist Approach to Offline Reinforcement Learning Scott Fujimoto S. Gu OffRL 114 816 0 12 Jun 2021
Who Is the Strongest Enemy? Towards Optimal and Efficient Evasion Attacks in Deep RL Yanchao Sun Ruijie Zheng Yongyuan Liang Furong Huang AAML 35 64 0 09 Jun 2021
Vector Quantized Models for Planning Sherjil Ozair Yazhe Li Ali Razavi Ioannis Antonoglou Aaron van den Oord Oriol Vinyals OffRL 61 50 0 08 Jun 2021
Robust Reinforcement Learning on State Observations with Learned Optimal Adversary Huan Zhang Hongge Chen Duane S. Boning Cho-Jui Hsieh 87 164 0 21 Jan 2021
Robust Deep Reinforcement Learning through Adversarial Loss Tuomas P. Oikarinen Wang Zhang Alexandre Megretski Luca Daniel Tsui-Wei Weng AAML 60 95 0 05 Aug 2020
Reinforcement Learning with Augmented Data Michael Laskin Kimin Lee Adam Stooke Lerrel Pinto Pieter Abbeel A. Srinivas OffRL 74 659 0 30 Apr 2020
Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels Ilya Kostrikov Denis Yarats Rob Fergus OffRL 92 789 0 28 Apr 2020
D4RL: Datasets for Deep Data-Driven Reinforcement Learning Justin Fu Aviral Kumar Ofir Nachum George Tucker Sergey Levine GP OffRL 210 1,359 0 15 Apr 2020
Robust Deep Reinforcement Learning against Adversarial Perturbations on State Observations Huan Zhang Hongge Chen Chaowei Xiao Yue Liu Mingyan D. Liu Duane S. Boning Cho-Jui Hsieh AAML 81 268 0 19 Mar 2020
Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models Pouya Samangouei Maya Kabkab Rama Chellappa AAML GAN 82 1,176 0 17 May 2018
Defense against Adversarial Attacks Using High-Level Representation Guided Denoiser Fangzhou Liao Ming Liang Yinpeng Dong Tianyu Pang Xiaolin Hu Jun Zhu 83 883 0 08 Dec 2017
Neural Discrete Representation Learning Aaron van den Oord Oriol Vinyals Koray Kavukcuoglu BDL SSL OCL 208 4,989 0 02 Nov 2017
Countering Adversarial Images using Input Transformations Chuan Guo Mayank Rana Moustapha Cissé Laurens van der Maaten AAML 102 1,400 0 31 Oct 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 277 12,029 0 19 Jun 2017
Delving into adversarial attacks on deep policies Jernej Kos D. Song AAML 59 225 0 18 May 2017
Domain Randomization for Transferring Deep Neural Networks from Simulation to the Real World Joshua Tobin Rachel Fong Alex Ray Jonas Schneider Wojciech Zaremba Pieter Abbeel 226 2,959 0 20 Mar 2017
Tactics of Adversarial Attack on Deep Reinforcement Learning Agents Yen-Chen Lin Zhang-Wei Hong Yuan-Hong Liao Meng-Li Shih Ming-Yuan Liu Min Sun AAML 74 413 0 08 Mar 2017
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 461 3,138 0 04 Nov 2016
Deep Reinforcement Learning with Double Q-learning H. V. Hasselt A. Guez David Silver OffRL 156 7,623 0 22 Sep 2015
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 247 14,893 1 21 Dec 2013